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Record W3112163797 · doi:10.1017/s146039692000103x

Dosimetric evaluation of SBRT treatment plans of non-central lung tumours: clinical experience

2020· article· en· W3112163797 on OpenAlexaffabout
Ernest Osei, Johnson Darko, Steph Swanson, Katrina Fleming, Ronald Snelgrove, Anmol Bhangu, Darin Gopaul

Bibliographic record

VenueJournal of Radiotherapy in Practice · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of GuelphGrand River HospitalUniversity of Waterloo
Fundersnot available
KeywordsMedicineTruebeamLung cancerNuclear medicineRadiation therapyRadiation treatment planningLungRadiologyRetrospective cohort studyRadiosurgerySurgeryOncologyLinear particle acceleratorInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objectives: Lung cancer is the most commonly diagnosed cancer in Canada and the leading cause of cancer-related mortality in both men and women in North America. Surgery is usually the primary treatment option for early-stage non-small cell lung cancer (NSCLC). However, for patients who may not be suitable candidates for surgery, stereotactic body radiation therapy (SBRT) is an alternative method of treatment. SBRT has proven to be an effective technique for treating NSCLC patients by focally administering high radiation dose to the tumour with acceptable risk of toxicity to surrounding healthy tissues. The goal of this comprehensive retrospective dosimetric study is to compare the dosimetric parameters between three-dimensional conformal radiation therapy (3DCRT) and volumetric-modulated arc therapy (VMAT) lung SBRT treatment plans for two prescription doses. Methods: We retrospectively analysed and compared lung SBRT treatment plans of 263 patients treated with either a 3DCRT non-coplanar or with 2–3 VMAT arcs technique at 48 Gy in 4 fractions (48 Gy/4) or 50 Gy in 5 fractions (50 Gy/5) prescribed to the planning target volume (PTV), typically encompassing the 80% isodose volume. All patients were treated on either a Varian 21EX or TrueBeam linear accelerator using 6-MV or 10-MV photon beams. Results: The mean PTV V95% and V100% for treatment plans at 48 Gy/4 are 99·4 ± 0·6% and 96·0 ± 1·0%, respectively, for 3DCRT and 99·7 ± 0·4% and 96·4 ± 3·4%, respectively, for VMAT. The corresponding mean PTV V95% and V100% at 50 Gy/5 are 99·0 ± 1·4% and 95·5 ± 2·5% for 3DCRT and 99·5 ± 0·8% and 96·1 ± 1·6% for VMAT. The CIRI and HI5/95 for the PTV at 48 Gy/4 are 1·1 ± 0·1 and 1·2 ± 0·0 for 3DCRT and 1·0 ± 0·1 and 1·2 ± 0·0 for VMAT. The corresponding CIRI and HI5/95 at 50 Gy/5 are 1·1 ± 0·1 and 1·3 ± 0·1 for 3DCRT and 1·0 ± 0·1 and 1·2 ± 0·0 for VMAT. The mean R50% and D2cm at 48 Gy/4 are 5·0 ± 0·8 and 61·2 ± 7·0% for 3DCRT and 4·9 ± 0·8 and 57·8 ± 7·9% for VMAT. The corresponding R50% and D2cm at 50 Gy/5 are 4·7 ± 0·5 and 65·5 ± 9·4% for 3DCRT and 4·7 ± 0·7 and 60·0 ± 7·2% for VMAT. Conclusion: The use of 3DCRT or VMAT technique for lung SBRT is an efficient and reliable method for achieving dose conformity, rapid dose fall-off and minimising doses to the organs at risk. The VMAT technique resulted in improved dose conformity, rapid dose fall-off from the PTV compared to 3DCRT, although the magnitude may not be clinically significant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.431
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2020
Admission routes2
Has abstractyes

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